SU‐E‐T‐32: Monte Carlo Determination of WAFAC Corrections for the Canadian LDR Primary Standard
Bibliographic record
Abstract
Purpose: Determine correction factors for a wide angle free‐air chamber (WAFAC) using Monte Carlo techniques for the realization of the air‐kerma strength, Sk, for low dose rate (LDR) 125 I and 103Pd brachytherapy sources. This WAFAC will become the Canadian primary standard for LDR brachytherapy sources. Methods: The EGSnrc user‐code egsfac is used for estimating the correction factors required to determine the air‐kerma at the WAFACs point of measurement (POM) using MC simulation for a 125 I and a 103Pd source. The geometry library egs++ allows simulation of the sources and the WAFAC in detail. Spectra are taken from the most recently published data. Air and aluminum attenuation curves for the 125 I seed were also measured with the WAFAC. Results: Correction values compared with those reported by NIST for its LDR primary standard (of very similar design) are in excellent agreement when using the NIST approach of assuming an isotropic point source and using experimental main spectrum lines. Differences in both methodologies for determining the WAFAC corrections are discussed and their impact evaluated. The effect of the source and the holder on the scatter correction is quantified separately. The calculations resulted in a modification of the design to reduce collimator transmission. A 3.2 mm lead sheet was added behind the WAFAC aperture, attenuating the 1251 and the 103Pd photon beams to less than 0.02 %. MC attenuation curves for air and aluminum for the 125 I seed are in good agreement with experimental data. The largest correction is the aluminum filter attenuation which can be as large as 4 %. Conclusion: Despite an inconsistency in the scatter estimation, the NIST approximation has little impact on the determination of Sk. The scatter correction is sensitive to the collimation system dimensions. Using MC‐based air and aluminum attenuation corrections for the 125 I seed is experimentally justified.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".